Couturier Stéphane, Galeana-Pizaña J Mauricio, Figueroa Daniela, Osorno-Covarrubias Javier, Jiménez Aldo Daniel
Laboratorio de Análisis Geo-Espacial (LAGE), Instituto de Geografía, Universidad Nacional Autónoma de México (UNAM), Circuito Exterior, Ciudad Universitaria, Del. Coyoacán, Apdo Postal 20850, Mexico CP 04510, Mexico.
Centro de Ciencias de la Complejidad (C3), UNAM, Mexico City, Mexico.
Data Brief. 2022 Aug 16;44:108543. doi: 10.1016/j.dib.2022.108543. eCollection 2022 Oct.
In this research, we build two food systems datasets in Mexico; The first one describes the structure of agricultural production units and the second one describes food security aspects of the rural population in these agricultural production units. We also build a third dataset, consisting of path diagrams and path coefficients (derived from Structural Equation Modeling) that relate the first dataset to the second dataset in the four most populated ecoregions of Mexico. The description of the path models and the insights they bring to the current state of food security in Mexican rural households are detailed in an associated article entitled "Is food security primarily associated with smallholder agriculture or with commercial agriculture?: An approach to the case of Mexico using structural equation modeling" (https://doi.org/10.1016/j.agsy.2021.103091). The agricultural variables (in the first dataset) include farm size, destination of the farmer's production, cultivation practice / water management, predominant source of income of the household, land tenure type, crop diversity, agricultural surface expansion, and the presence of forest cover. They are based on the primary data of the full, latest available agricultural census in Mexico and corresponding official land use / land cover data. The second dataset consists of four food security indicators designed and built for the first food security model in Mexico that incorporates food availability, food accessibility and food utilization aspects. They include the Food Self-sufficiency Index (the balance between food production and food consumption), the Food Access Index (inversely related to marginalization), the Entitlement to Public Health Care index, and the Undernutrition Infrequency index (related to hospital sickness records). We provide the path tables and diagrams that describe the links between the agricultural structure and food security. These diagrams provide the first nationwide statistical evidence for the prominent role of smallholder agriculture in rural food security at the national level and at ecoregion scale for a country of the global South. In order to further investigate the structure of the agricultural production units and their relationships with socio-economic, territorial and landscape data, artificial intelligence (i.e. data mining and machine learning) techniques could be performed on this compendium of datasets. The food security data may stir the development of more food security models in Mexico in relation to other drivers such as consumption habits and non-agricultural activities of rural households.
在本研究中,我们构建了墨西哥的两个粮食系统数据集;第一个描述了农业生产单位的结构,第二个描述了这些农业生产单位中农村人口的粮食安全状况。我们还构建了第三个数据集,由路径图和路径系数(源自结构方程模型)组成,这些路径图和路径系数将墨西哥人口最多的四个生态区域中的第一个数据集与第二个数据集联系起来。路径模型的描述以及它们对墨西哥农村家庭当前粮食安全状况的见解,在一篇题为《粮食安全主要与小农农业还是商业农业相关?:使用结构方程模型对墨西哥案例的一种研究方法》(https://doi.org/10.1016/j.agsy.2021.103091)的相关文章中有详细阐述。(第一个数据集中的)农业变量包括农场规模、农民生产的去向、种植实践/水资源管理、家庭主要收入来源、土地保有权类型、作物多样性、农业面积扩张以及森林覆盖情况。它们基于墨西哥最新可得的全面农业普查的原始数据以及相应的官方土地利用/土地覆盖数据。第二个数据集由为墨西哥第一个粮食安全模型设计和构建的四个粮食安全指标组成,该模型纳入了粮食供应、粮食可及性和粮食利用等方面。它们包括粮食自给自足指数(粮食生产与粮食消费之间的平衡)、粮食可及指数(与边缘化程度呈负相关)、公共医疗保健权利指数以及营养不良发生率指数(与医院疾病记录相关)。我们提供了描述农业结构与粮食安全之间联系的路径表和路径图。这些图为小农农业在全球南方一个国家的国家层面和生态区域尺度上对农村粮食安全的突出作用提供了首个全国性统计证据。为了进一步研究农业生产单位的结构及其与社会经济、地域和景观数据的关系,可以对这个数据集汇编应用人工智能(即数据挖掘和机器学习)技术。粮食安全数据可能会推动墨西哥针对农村家庭的消费习惯和非农业活动等其他驱动因素开发更多粮食安全模型。